Today marked the conclusion of VentureBeat's Transform 2020 summit, which took place online for the first time in our history. Luminaries including Google Brain ethicist Timnit Gebru and IBM AI ethics leader Francesca Rossi spoke about how women are advancing AI and leading the trend of AI fairness, ethics, and human-centered AI. Twitter CTO Parag Agrawal detailed the social network's efforts to apply AI to detect fake or hateful tweets. Pinterest SVP of technology Jeremy King walked through learnings from Pinterest's explorations of computer vision to create "inspirational" experiences. And Unity principal machine learning engineer Cesar Romero brought clarity to the link between synthetic data sets and real-world AI model training.

The Nest Learning Thermostat uses behavioral algorithms to save energy based on your behavior and schedule. It employs a very intelligent machine-learning process that learns the temperature you like and programs itself in about a week. As a result, it will automatically turn off to save energy if nobody is at home.

The industry is far from ready to take humans "out of the loop" on most security operations and let machines run our cyber-defenses autonomously. However, machine learning breakthroughs are already making huge strides in reducing compromises as well as easing the burden of security staff in investigating suspicious events. These under-staffed teams are often overwhelmed with massive volumes of alerts, making it tough to weed out false alarms and identify the subtle signs of more sophisticated attacks. Machine learning anti-malware systems draw on deep knowledge of malware from analyzing millions of malicious samples. Cloud computing horsepower and data science techniques help master the "DNA" and "family trees" of malware, so even completely new malware is accurately detected.